Data Science will change the marketing world as we know it

Big Data. It’s one of those terms that is now so widely–and indiscriminately–used in the business world that even the least cynical among us are probably getting sick of it. It’s a term that is used to fill in gaps during meetings and to make people sound as if they are up to date with digital technology.

The thing about “Big Data,” however, is that it is not a meaningless cliché. It is overused and sometimes misused. Digital technology has replaced the analog world in which we used to work and flooded us with data. The more advanced digital technology becomes, the easier it is for us to share information with others or track their buying habits. More data is being generated.

In 2013, IBM stated that 90% of all data created today in the world was created within the past two years. Cisco predicted in 2015 that data creation in 2019 would surpass the data generated in the previous Internet years. In two years, it is estimated that each individual will produce 1.7 Megabytes every second.

Big Data is…well… an enormous amount of information. Information that can be collected, analyzed, and stored (which is the widely accepted definition of data).

Is there another more precise meaning? What are the marketing implications?

Big Data: A more specific definition?

According to a Word Sleuth by the New York Times, “Big Data” was used in Silicon Valley in the 1990s.

In 1997, NASA referred to the problem it faced as: “[It is] an interesting challenge to computer systems. Data sets are usually quite large and tax the capacity of main memory, the local disk, or even the remote disk. This is the “problem of big data.”

Although there is no consensus on the definition of “Big Data,” most definitions do mention the problem of large datasets. The problem is not just the logistical challenges of storing the data but also the difficulty of sorting and analyzing the massive amounts of data.

Other definitions of Big Data are less formal. We’re awash in numbers, statistics, demographics, and more, but we can harness these to build an analytical picture that’s superior to anything else we’ve seen in any discipline. To quote data experts in a blog, “more data can be better if you know how to use it.”

How does Big Data apply to marketing?

Big Data is used in marketing in many different ways. Here are some of the most significant:

1. Advertising and content. While the digital revolution has complicated the process of promoting products with new media, platforms, and techniques, it’s also made it easier to track and monitor the effectiveness of the promotion. A data scientist who is able to use digital information can help an organization experiment with their advertising and content. They will be able to identify which methods and messages resonate with customers and which do not. Then there’s the vast field of customer insight, which deserves its article.

2. Pricing. Professional data analysis can transform the way companies approach pricing. McKinsey reported in 2014 that ” 30% percent of the pricing decisions made by companies each year do not deliver the best prices.” The solution it offered was data analysis. “For those who are able to bring some order to the complexity of big data, the value can be substantial.”

3. The McKinsey report on optimizing spending said, “In the past, such decisions were made based on a small amount of data and a great deal of gut feeling.” The “new world,” according to McKinsey, allows businesses to use “advanced analytics–particularly more real-time data–[to] eliminate much of the guesswork” when attempting to ensure spend is spot on for any number of marketing activities: from social media to call-center investment, or traditional advertising to store fit-outs.

4. We’re starting to see examples all over the world of Big Data being used as an extraordinary tool for prediction and trend forecasting. In many parts of the world, we are starting to see big data as a tool for trend prediction.

The website says: “Forget about copycat trends or corporate espionage. Forget about stealing your competitor’s top workers.” Data science is the use of information that is already available, information that shows the direction in which a trend will take.

All of these things are related: Information alone is useless in an age where half of the world’s population has Internet access and 50 billion devices have been connected via the Internet of Things.

Data scientists are, therefore, critical. There aren’t nearly enough data scientists.

Data Scientists: Precious Resources?

The market has told us that Big Data is not a fad.

There are massive shortages of data scientists around the globe, even though it’s been over half a century since the Harvard Business Review dubbed the role ” the Sexiest Job in the 21st Century”. There are not enough professionals to separate the wheat from the chaff.

CrowdFlower published a 2016 report on data science, and 83% of American data scientists surveyed said there was a shortage of people qualified to work in their fields. In 2017, it produced a report similar to the 2016 one but did not ask the same questions. Instead, they asked about how “in-demand” respondents were. Data scientists were contacted by 89% for at least one new job opportunity per month; 30% were contacted multiple times a day.

As the CrowdFlower Study suggests, the market gap is not only a problem for businesses but also for those who are planning to become data scientists in the near future.

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